Pine wilt disease (PWD) is a pine tree disease that caused by pinewood nematode Bursaphelenchus xylophilus. It is considered a dramatic disease because it kills affected trees within a few week to a few month. The vector for the pine wild trees is pine sawyer beetle (or Monochamus alternatus). This pine wood disease caused by the pinewood nematode was firstly investigated in 1905 in Japan. In 1980s, the pine wilt disease epidemic had spread to other Asian countries, such as Honk Kong, Korea, China and Taiwan. In 1999, PWD reached to Portugal. The first observable symptom is the lack of resin exudation (the abundant flow of resin from coniferous trees) from bark wounds. The foliage then becomes pale green, then yellow, and finally reddish brown as the tree succumbs to the disease. One occurs during maturation feeding, when the nematode is transferred from insect vectors to healthy pine trees via the insect feeding on wounds. The second occurs during oviposition of the mature female on dead, dying, or recently cut pine trees via the oviposition wounds. The third occurs during mating, that is, as mature males search for females in bark wounds, such as the oviposition wounds. This is referred to as horizontal transmission.
A mathematical model for the spread of pine wilt disease with variable population size
The model is locally as well as globally asymptotically stable.
Formulation of an optimal control problem
Tree injection, deforestation, and aerial insecticide spraying
Due to the significant role in industry and engineering, it is very important to study the flow behavior of Newtonian, non-Newtonian and nanofluids. The study of MHD flow of Newtonian, non-Newtonian and nanofluids in a porous medium with and without combined effects of heat and mass transfer are improtant areas. The customary models of Newtonian and non-Newtonian fluids via fractional calculus may be generalized using the concepts of fractional deravivatives. This reseaech will cover various flow regimes and their solutions, including, Newtonian, non-Newtonian and nanofluids via integral transforms and numerical schemes.
1. Mathematicsl Modelling
2. Generalization of the Models
3. Applications to Real World problems.
4. Solutions of the Problems
In the industrial estate where lot of industries, mineral spread dust particles in the open environment. The dust particles are called waste or the fly ash. For economic and environmental aspect the industrial waste reuse is appreciable contamination is the major issue of environment. This study was under taken to the mechanical use fly ash as partial replacement of other produce and et of building ------- as partial replacement for fine aggregates in cement mortar at various percentages by weight of the cement and fine aggregate) with water. An experimental investigation for the measurement of consistency, initial setting time and final setting time of cement with fins dust ash replacement were determined. Consistency of dust (Workability) called fly ash and waste of mineral dust replacement was determined by using flow table test. Cubes of the samples with fly ash dust content and waste marble dust replacement as to determine the compressive strength of hardened cement mortar. The test results showed that addition of dust ash and waste marble dust into cement mortar mixture significantly increased its compressive strength, initial setting time, final setting time and consistency of cement mortar, while consistency of cement was decreased as compared to conventional. This study relates that reusing of dust of minerals ash and waste marble dust as substitutes in gives a alternate use of mineral dust approach.
Usually exchange of ideas bring a new concept to form.Big data was initially originated on lunch
table conversation at silicon graphics Inc. in the mid-1990's.The term widespread as recently as
in 2011."Small and midsize companies in developed companies look to make big gains with big
data," 2012. Size is the first characteristic of big data. However, other characteristics includes the
three V's, Volume, Variety and Velocity (Laney, 2001; Kwon, Lee, & Shin, 2014).
"Big data is high-volume, high-velocity and high-variety information assets that demand cost-
effective, innovative forms of information processing for enhanced insight and decision
making." (Gartner IT Glossary, n.d.).
Recently, in addition to the three V's, other dimensions of big data have also emerged which includes Veracity, Variability and Value. There is no benchmark set for volume, variety and velocity that defines big data. The limits totally depends upon the sector, size and location of the institution and these limits evolve and change over the time.A very important fact is that these dimensions are not independent of each other. If one increases other will also automatically increase.
Big data in a vacuum is worthless. Its potential is unleashed when it is used to support decision formulation. It is about collecting and interrogate complete datasets to generate objective patterns and impression out of it. New correlations and conclusion can be established in the sea of data. Big data won't oppress creativity and innovation but it will find surprising uses of it. For instance, in banking, number of cards swipes, and number of times a card swiped can help to determine the behavior of the customers. Sentiment analysis, spending behavior of customer, main channels of transactions, customer segmentation, Fraud management and prevention, risk assessment and reporting can be done with help of big data. There are many other correlations which can be found in future to support the industry. Big data starts with the explosion of data that we have generated. These explosion leads to design and patterns where new opportunities are generated out of these patterns. These patterns need to be very imaginative to compete with the challenges the country is facing. Henry ford
asked the public what they wanted, and they demanded faster horses. He was imaginative enough to convert those fast horses into automobiles. Such imaginative contributions are required to flourish the country. Global indices can help to identify the potential areas where the efforts can be put in and the scope is broader.
The increasing race in technology, industry and businesses is compelling institutions to find
alternatives and effective ways of research for commercial use. This debate begins with an
assumption that the universities will command the scientific and technological research
resources. The research work will be taken up by the industry and converted into products and
services. Whereas, the industry will also address the concerns of the academia.
As a nation, we strongly believe that the higher education cannot operate in isolation on islands
of knowledge; it has no value unless it is dispensed and concentrated on the current and future
needs. For this reason, the knowledge-islands need to be connected to the cluster of businesses
The purpose of this proposal is to understand:
How knowledge integrated community can be developed for context and result driven researches?
How government can support this KIC programmes at National and Provincial level for context and result driven researches?
Comparison of Pakistan with other Asian countries
Pakistan has been known as exporter of agricultural products. In addition to it, leather and textile is also a major export contributor in the GDP. Whereas the industrial sector is way behind
because of unavailability of skilled work force and infrastructure. The public and private sector are having poor research and development centers and they lack in academia linkages. Korea and Singapore have emerged as a developed countries have ensured the academic support to the industrial sector. This support help in the excellence in their production and exports and to lead with their counter parts. Thailand have emerged as a developed nation. This revival is because of explicitly focusing on the academia-industry linkages. Similarly there 66 initiatives in fabric design, dyeing & printing, supply chain management and IT is a product of universities interm of their research and development projects. China among their other Asian countries, have strongly focused on academia and industry linkage strategy. China being the second largest nation in the world has accelerated its growth is last two decades. It is not only because of linking academia and industry but the mutual setting of aligning results with progress and reforms which leads to boom in china economy. Singapore and Malaysia have realized the significance of academia-industry linkages. Singapore was considered as developed state by 1990's. However, they bridged the gap between academia and industry before a decade. Malaysia development is different as compared to Singapore but they are ahead of Pakistan interms of academia-industry linkages. Malaysia